• Journal of Korean Society of Transportation
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• v.14 no.3
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• pp.127-141
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• 1996

This paper presents a unique approach to urban traffic network signal control. This paper begins with an introduction to traffic control in general, and then goes on to describe the approach of fuzzy control, where the signal timing parameters at a given intersection are adjusted as functions of the local traffic network condition and adjacent intersection. The signal timing parameters evolve dynamically using only local information to improve traffic signal flow. The signal timing at an intersection is defined by three parameters : cycle time, phase split, off set. Fuzzy decision rules are used to adjust three parameters based only on local information. The amount of change in the timing parameters during each cycle is limited to a small fraction of the current parameters to ensure smooth transition. In this paper the effectiveness of this method is showed through simulation of the traffic signal flow in a network of controlled intersection.

• Journal of Advanced Navigation Technology
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• v.21 no.5
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• pp.472-478
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• 2017

In this paper, we deals with optimizing traffic signal timing in grid networks by using a network topology design method. Optimizing traffic signal timing includes minimizing delay time delay between departure and destination by interlocking straight traffic signal in the minimum spanning tree(MST). On the assumption that users of network abide by the paths provided in this paper, this paper shows optimizing traffic signal timing in grid networks. the paths provided in this paper is gathered by using Dijkstra algorithm used in computer networks. The results indicate minimizing delay time of passing through the grid network and interlocking traffic signal in the grid network.

• Journal of the Korean Operations Research and Management Science Society
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• v.24 no.2
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• pp.69-80
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• 1999

A genetic algorithm to determine the optimal signal sequence and double cycle pattern is described. The signal sequence and double cycle pattern are used as the input for TRANSYT to find optimal signal timing at each junction in the area traffic networks, In the genetic process, the partially matched crossover and simple crossover operators are used for evolution of signal sequence and double cycle pattern respectively. A special conversion algorithm is devised to convert the signal sequence into the link-stage assignment for TRANSYT. Results from tests using data from an area traffic network in Leicester region R are given.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4268-4289
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• 2020

Advanced traffic signal timing method plays very important role in reducing road congestion and air pollution. Reinforcement learning is considered as superior approach to build traffic light timing scheme by many recent studies. It fulfills real adaptive control by the means of taking real-time traffic information as state, and adjusting traffic light scheme as action. However, existing works behave inefficient in complex intersections and they are lack of feasibility because most of them adopt traffic light scheme whose phase sequence is flexible. To address these issues, a novel adaptive traffic signal timing scheme is proposed. It's based on actor-critic reinforcement learning algorithm, and advanced techniques proximal policy optimization and generalized advantage estimation are integrated. In particular, a new kind of reward function and a simplified form of state representation are carefully defined, and they facilitate to improve the learning efficiency and reduce the computational complexity, respectively. Meanwhile, a fixed phase sequence signal scheme is derived, and constraint on the variations of successive phase durations is introduced, which enhances its feasibility and robustness in field applications. The proposed scheme is verified through field-data-based experiments in both medium and high traffic density scenarios. Simulation results exhibit remarkable improvement in traffic performance as well as the learning efficiency comparing with the existing reinforcement learning-based methods such as 3DQN and DDQN.

• Journal of Korean Society of Transportation
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• v.5 no.2
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• pp.19-35
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• 1987

Transportation energy saving is a national concern because all national petroleum energy is imported. A number of intersections are operating as semi-protected intersections, which have left-turn signal but not exclusive left-turn lanes, because of limited roadways in urban areas. Since the traffic signal methods for the intersections having left-turn signal/lanes cannot be applied to the semi-protected intersection, it is needed to develop a new technique. The purpose of this study was to develop a traffic signal timing method at semi-protected intersections for energy saving and to computerize the method for the practical use. A probability model which could estimate left-turn utilization factors of through traffic during green signal was developed based on field studies. Employing the factors, macro-models to estimate vehicular average delay and proportions of vehicles stopped at the semiprotected intersections were developed. The calculated values of the delay model agreed well with the simulated values of a simulation model using SLAM Ⅱ, a simulation language. Using the two models and the idling fuel consumption rate and the excess fuel consumption per stop-go speed change of vehicles. a traffic signal timing method at semi-protected intersections for energy saving was developed and computerized. The method can be used for other measures of effectiveness such as minimum delay, minimum stop ratio, etc.

• Journal of Korean Society of Transportation
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• v.8 no.1
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• pp.25-40
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• 1990

This study was undertaken to develop a traffic signal timing method for interconnected and semi-protected-left-turn intersections(the intersections which have left-turn signal but not exclusive left-turn lanes) on four-lane streets for energy saving and to computerize the method for the practical use. For this study, a probability model which could estimate the utilized time of the shared left-turn lane by through traffic during green period was developed based on field studies. The two left-turn treatments, leading and lagging left-turns, were tested for the intersections, and it can be concluded that the leading left-turn was more efficient for the normal urban streets on which through traffic is major traffic. Adopting the leading left-turn macro-models to estimate vehicular average delay and proportions of vehicles stopped at the intersections were developed. Using the two models as well as the idling fuel consumpution rate and the excess fuel consumption per stop-go speed change, a traffic signal timing method for the intersections for energy saving was developed and computerized. The method can be used for more than four-lane streets and for other measures of effectiveness such as minimum delay, minimum stop rates, etc.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.81-92
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• 2023

Traffic state classification is crucial for time-of-day (TOD) traffic signal control. This paper proposed a traffic state classification technique applying Deep-Embedded Clustering (DEC) method that uses a high dimensional traffic data observed at all signalized intersections in a traffic signal control sub area (SA). So far, signal timing plan has been determined based on the traffic data observed at the critical intersection in SA. The current method has a limitation that it cannot consider a comprehensive traffic situation in SA. The proposed method alleviates the curse of dimensionality and turns out to overcome the shortcomings of the current signal timing plan.

• Journal of Korean Society of Transportation
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• v.19 no.1
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• pp.115-129
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• 2001

The purpose of this study is to develop a cycle-free signal timing model for minimizing delays based on Third-generation control concept using Genetic Algorithm. A special feature of this model is its ability to manage delays of turning movements on the cycle basis. The model produces a cycle-free based signal timing(cycles and green times) for each intersection to minimize delays of turning movements on the cycle basis. The performance of cycle-free signal timings was evaluated on normal (v/c = 0.7) and oversaturated (v/c=1.0) conditions. The performance measures are throughput and the number of queued vehicles at the end of green time. The result shows that the cycle free signal timing is superior to the fixed signal timing to manage traffic flows of intersections; (1) the proposed model accomplishes the basic objective of the research, producing cycle free signal timings on the cycle basis, (2) on normal conditions, cycle free signal timings produce less queued vehicles at the end of green time, and (3) on oversaturated conditions, the cycle free signal timing is superior to the fixed signal timing to manage saturated traffic flows of intersections.

• Journal of Auto-vehicle Safety Association
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• v.14 no.3
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• pp.48-59
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• 2022

A V2X system can be a candidate as a means to increase the stability of autonomous vehicles. In particular, in order to implement a Level 4 or higher autonomous driving system, the application of the V2X system is essential. Wireless communication technologies applicable to the V2X system include WAVE and C-V2X. Currently, the V2X service most used by autonomous driving systems is a service that provides signal phase and timing information and since real-time characteristic is a very important, verification of this service must be done. In this paper, we measured the time delay characteristics for providing signal phase and timing information using WAVE and LTE communication, and proposed a TOD-based signal phase and timing information generation method without using V2X communication system. To analyze the time delay characteristics, RTT (Round Trip Time) was measured as a result of the measurement. Average RTT using WAVE communication was 5.84ms and was 104.15ms with LTE communication. As a result of measuring the error between the signal phase and timing information generated based on TOD and the actual traffic light state, it was measured to be -0.284~3.784sec.

• Journal of the Korea Society for Simulation
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• v.6 no.2
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• pp.15-29
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• 1997

Many studies have been performed and applied successfully for the control of undersaturated intersections, but most of them have been ineffective or invalid in oversaturated conditions. There has been relatively limited research in traffic control for oversaturated environments, and most has been too theoretical to be applied in a real system. Therefore, a traffic simulation model specifically designed for oversaturated arterial networks was developed. Two control objectives of traffic signal timing in oversaturated conditions were taken into consideration. One was to maximize the throughput, or the number of vehicles processed during a given time period. The other was to prevent queue spillback or to minimize the occurrence of queue spillback if inevitable.